2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)最新文献_第7页

New Approach of Cycling Phases Detection to Improve FES-Pedaling in SCI Individuals 循环阶段检测改善脊髓损伤患者fes - pedal的新方法

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8594162

R. Baptista, Benoît Sijobert, C. Azevedo

引用次数: 6

Unit Quaternion-Based Parameterization for Point Features in Visual Navigation 基于单元四元数的视觉导航点特征参数化

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8594206

James Maley, G. Huang

引用次数: 5

Improved Quadcopter Disturbance Rejection Using Added Angular Momentum 利用增加角动量改进四轴飞行器抗扰性能

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8594109

Nathan Bucki, M. Mueller

引用次数: 6

Implementation of a Versatile 3D ZMP Trajectory Optimization Algorithm on a Multi-Modal Legged Robotic Platform 多模态足式机器人平台上通用三维ZMP轨迹优化算法的实现

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8593968

Joshua Hooks, D. Hong

引用次数: 11

“Oh! I am so sorry!”: Understanding User Physiological Variation while Spoiling a Game Task “哦!我很抱歉!:在破坏游戏任务的同时理解用户的生理变化

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8593395

Roxana Agrigoroaie, Arturo Cruz-Maya, A. Tapus

引用次数: 4

Cloud services for robotic nurses? Assessing legal and ethical issues in the use of cloud services for healthcare robots 机器人护士的云服务?评估医疗保健机器人使用云服务的法律和道德问题

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8593591

E. Fosch-Villaronga, H. Felzmann, M. Ramos-Montero, T. Mahler

{"title":"Cloud services for robotic nurses? Assessing legal and ethical issues in the use of cloud services for healthcare robots","authors":"E. Fosch-Villaronga, H. Felzmann, M. Ramos-Montero, T. Mahler","doi":"10.1109/IROS.2018.8593591","DOIUrl":"https://doi.org/10.1109/IROS.2018.8593591","url":null,"abstract":"This paper explores ethical and legal implications arising from the intertwinement of cloud services, healthcare and robotics. It closes an existing gap in the literature by highlighting the distinctive ethical and legal concerns associated with the inter-dependence of the cyber- and the physical aspects of healthcare cloud robotics. The identified core concerns include uncertainties with regard to data protection requirements; distributed responsibilities for unintended harm; achievement of transparency and consent for cloud robot services especially for vulnerable robot users; secondary uses of cloud data derived from robot activities; data security; and wider social issues. The paper aims to raise awareness and stimulate reflection of the legal and ethical impacts on different stakeholders arising from the use of cloud services in healthcare robotics. We show that due to the complexity of these concerns the design and implementation of such robots in healthcare requires an interdisciplinary development and impact assessment process. In light of legal requirements and ethical responsibilities towards end-users and other stakeholders, we draw practical considerations for engineers developing cloud services for robots in healthcare.","PeriodicalId":6640,"journal":{"name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"2 1","pages":"290-296"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86603815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 19

Towards an Automatic Spasticity Assessment by Means of Collaborative Robots 基于协作机器人的痉挛自动评估

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8594158

Mar Hernandez, E. Oña, J. Garcia-Haro, Alberto Jardón Huete, C. Balaguer

{"title":"Towards an Automatic Spasticity Assessment by Means of Collaborative Robots","authors":"Mar Hernandez, E. Oña, J. Garcia-Haro, Alberto Jardón Huete, C. Balaguer","doi":"10.1109/IROS.2018.8594158","DOIUrl":"https://doi.org/10.1109/IROS.2018.8594158","url":null,"abstract":"Robotics can play a significant role in the rehabilitation of patients with spasticity by improving their early diagnosis and reducing the costs associated with care. Spasticity is a muscle control disorder characterized by an increase in muscle tone with exaggerated stretch reflexes, as one component of the upper motor neuron syndrome. Furthermore, spasticity is present in other pathologies, such as cerebral palsy, spina bifida, brain stroke among others. This video shows the ongoing research on developing a platform for the modelling and the assessment of spasticity using collaborative robots as clinical tool. Our aim is to develop methods for non-invasive biomechanical modelling of upper limbs joints using 7-DOF Rosen Kinematics [1], mixed with a non-linear state of Hills force-velocity relation [2], improved by introducing new parameters such as rigidity, viscoelasticity, extensibility and thixotropy. After a learning phase performed by the therapist, the robot replicates the trajectories required to perform the assessment. The video also describes the detailed analysis of passive movement response (force/torque and position/velocity)of the limb. These parameters will be used to determine the degree of spasticity of patients in a fast and objective manner, while simultaneously developing new clinical scales, such as a modified version of Ashworth [3].","PeriodicalId":6640,"journal":{"name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"9 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88897082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Robotic Handling of Compliant Food Objects by Robust Learning from Demonstration 机器人处理柔顺食品对象的鲁棒学习演示

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8594368

E. Misimi, Alexander Olofsson, A. Eilertsen, Elling Ruud Øye, J. R. Mathiassen

{"title":"Robotic Handling of Compliant Food Objects by Robust Learning from Demonstration","authors":"E. Misimi, Alexander Olofsson, A. Eilertsen, Elling Ruud Øye, J. R. Mathiassen","doi":"10.1109/IROS.2018.8594368","DOIUrl":"https://doi.org/10.1109/IROS.2018.8594368","url":null,"abstract":"The robotic handling of compliant and deformable food raw materials, characterized by high biological variation, complex geometrical 3D shapes, and mechanical structures and texture, is currently in huge demand in the ocean space, agricultural, and food industries. Many tasks in these industries are performed manually by human operators who, due to the laborious and tedious nature of their tasks, exhibit high variability in execution, with variable outcomes. The introduction of robotic automation for most complex processing tasks has been challenging due to current robot learning policies. A more consistent learning policy involving skilled operators is desired. In this paper, we address the problem of robot learning when presented with inconsistent demonstrations. To this end, we propose a robust learning policy based on Learning from Demonstration (LfD) for robotic grasping of food compliant objects. The approach uses a merging of RGB-D images and tactile data in order to estimate the necessary pose of the gripper, gripper finger configuration and forces exerted on the object in order to achieve effective robot handling. During LfD training, the gripper pose, finger configurations and tactile values for the fingers, as well as RGB-D images are saved. We present an LfD learning policy that automatically removes inconsistent demonstrations, and estimates the teacher's intended policy. The performance of our approach is validated and demonstrated for fragile and compliant food objects with complex 3D shapes. The proposed approach has a vast range of potential applications in the aforementioned industry sectors.","PeriodicalId":6640,"journal":{"name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"95 1","pages":"6972-6979"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88840047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Embedding Temporally Consistent Depth Recovery for Real-time Dense Mapping in Visual-inertial Odometry 视觉惯性里程计中实时密集映射的时间一致深度恢复嵌入

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8593917

Hui Cheng, Zhuoqi Zheng, Jinhao He, Chongyu Chen, Keze Wang, Liang Lin

{"title":"Embedding Temporally Consistent Depth Recovery for Real-time Dense Mapping in Visual-inertial Odometry","authors":"Hui Cheng, Zhuoqi Zheng, Jinhao He, Chongyu Chen, Keze Wang, Liang Lin","doi":"10.1109/IROS.2018.8593917","DOIUrl":"https://doi.org/10.1109/IROS.2018.8593917","url":null,"abstract":"Dense mapping is always the desire of simultaneous localization and mapping (SLAM), especially for the applications that require fast and dense scene information. Visual-inertial odometry (VIO) is a light-weight and effective solution to fast self-localization. However, VIO-based SLAM systems have difficulty in providing dense mapping results due to the spatial sparsity and temporal instability of the VIO depth estimations. Although there have been great efforts on real-time mapping and depth recovery from sparse measurements, the existing solutions for VIO-based SLAM still fail to preserve sufficient geometry details in their results. In this paper, we propose to embed depth recovery into VIO-based SLAM for real-time dense mapping. In the proposed method, we present a subspace-based stabilization scheme to maintain the temporal consistency and design a hierarchical pipeline for edge-preserving depth interpolation to reduce the computational burden. Numerous experiments demonstrate that our method can achieve an accuracy improvement of up to 49.1 cm compared to state-of-the-art learning-based methods for depth recovery and reconstruct sufficient geometric details in dense mapping when only 0.07% depth samples are available. Since a simple CPU implementation of our method already runs at 10–20 fps, we believe our method is very favorable for practical SLAM systems with critical computational requirements.","PeriodicalId":6640,"journal":{"name":"2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"8 1","pages":"693-698"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88951565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

After You: Doorway Negotiation for Human-Robot and Robot-Robot Interaction 在你之后:人-机器人和机器人-机器人交互的门口谈判

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2018-10-01 DOI: 10.1109/IROS.2018.8594034

Jack Thomas, R. Vaughan

引用次数: 14